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Arabidopsis (Arabidopsis thaliana) primary and lateral roots (LRs) are well suited for 3D and 4D microscopy, and their development provides an ideal system for studying morphogenesis and cell proliferation dynamics. With fast-advancing microscopy techniques used for live-imaging, whole tissue data are increasingly available, yet present the great challenge of analyzing complex interactions within cell populations. We developed a plugin “Live Plant Cell Tracking” (LiPlaCeT) coupled to the publicly available ImageJ image analysis program and generated a pipeline that allows, with the aid of LiPlaCeT, 4D cell tracking and lineage analysis of populations of dividing and growing cells. The LiPlaCeT plugin contains ad hoc ergonomic curating tools, making it very simple to use for manual cell tracking, especially when the signal-to-noise ratio of images is low or variable in time or 3D space and when automated methods may fail. Performing time-lapse experiments and using cell-tracking data extracted with the assistance of LiPlaCeT, we accomplished deep analyses of cell proliferation and clonal relations in the whole developing LR primordia and constructed genealogical trees. We also used cell-tracking data for endodermis cells of the root apical meristem (RAM) and performed automated analyses of cell population dynamics using ParaView software (also publicly available). Using the RAM as an example, we also showed how LiPlaCeT can be used to generate information at the whole-tissue level regarding cell length, cell position, cell growth rate, cell displacement rate, and proliferation activity. The pipeline will be useful in live-imaging studies of roots and other plant organs to understand complex interactions within proliferating and growing cell populations. The plugin includes a step-by-step user manual and a dataset example that are available at https://www.ibt.unam.mx/documentos/diversos/LiPlaCeT.zip.

Asymmetric cell divisions are essential to generate different cellular lineages. In plants, asymmetric cell divisions regulate the correct formation of the embryo, stomatal cells, apical and root meristems, and lateral roots. Current knowledge of regulation of asymmetric cell divisions suggests that, in addition to the function of key transcription factor networks, epigenetic mechanisms play crucial roles. Therefore, we highlight the importance of epigenetic regulation and chromatin dynamics for integration of signals and specification of cells that undergo asymmetric cell divisions, as well as for cell maintenance and cell fate establishment of both progenitor and daughter cells. We also discuss the polarization and segregation of cell components to ensure correct epigenetic memory or resetting of epigenetic marks during asymmetric cell divisions.

Gene essentiality estimation is a popular empirical approach to link genotypes to phenotypes. In humans, essentiality is estimated based on loss-of-function (LoF) mutation intolerance, either from population exome sequencing (in vivo) data or CRISPR-based in vitro perturbation experiments. Both approaches identify genes presumed to have detrimental consequences on the organism upon mutation. Are these genes constrained by having key cellular/organismal roles? Do in vivo and in vitro estimations equally recover these constraints? Insights into these questions have important implications in generalizing observations from cell models and interpreting disease risk genes. To empirically address these questions, we integrate genome-scale datasets and compare structural, functional and evolutionary features of essential genes versus genes with extremely high mutational tolerance. We found that essentiality estimates do recover functional constraints. However, the organismal or cellular context of estimation leads to functionally contrasting properties underlying the constraint. Our results suggest that depletion of LoF mutations in human populations effectively captures organismal-level functional constraints not experimentally accessible through CRISPR-based screens. Finally, we identify a set of genes (OrgEssential), which are mutationally intolerant in vivo but highly tolerant in vitro. These genes drive observed functional constraint differences and have an unexpected preference for nervous system expression.

Flowering is one of the most critical developmental transitions in plants’ life. The irreversible change from the vegetative to the reproductive stage is strictly controlled to ensure the progeny’s success. In Arabidopsis thaliana, seven flowering genetic pathways have been described under specific growth conditions. However, the evidence condensed here suggest that these pathways are tightly interconnected in a complex multilevel regulatory network. In this review, we pursue an integrative approach emphasizing the molecular interactions among the flowering regulatory network components. We also consider that the same regulatory network prevents or induces flowering phase change in response to internal cues modulated by environmental signals. In this sense, we describe how during the vegetative phase of development it is essential to prevent the expression of flowering promoting genes until they are required. Then, we mention flowering regulation under suboptimal growing temperatures, such as those in autumn and winter. We next expose the requirement of endogenous signals in flowering, and finally, the acceleration of this transition by long-day photoperiod and temperature rise signals allowing A. thaliana to bloom in spring and summer seasons. With this approach, we aim to provide an initial systemic view to help the reader integrate this complex developmental process.

In the present work we propose a mathematical model of the process of inflammation in lung cells in response to SARS-CoV-2 infection from which a plausible scenario for the dynamics of this process arise. In this scenario the main protease Nsp5 enhances the inflammatory process, increasing the levels of NF kappaB, IL-6, Cox2, and PGE2 with respect to a reference state without the virus. When in presence of the virus the translation rates of NF kappaB and IkB are increased to a high constant value, and the translation rate of IL-6 is increased above the threshold value of 7 nM s-1, the model predicts a persistent over stimulated immune state with high levels of the cytokine IL-6. This over stimulated immune state becomes autonomous of the signals from other immune cells like macrophages and lymphocytes, and does not shut down by itself. Dexamethasone or Nimesulide have little effect on this state of the infected lung cell, and the only form to suppress it is with the inhibition of the activity of the viral protein Nsp5 with drugs like Saquinavir. In this form, our model suggests that Nsp5 is effectively the cause of the severe acute lung inflammation during SARS-CoV-2 infection. The persistent production of IL-6 by lung cells can be one of the causes of the cytokine storm observed in critical patients with COVID19. From an evolutive point of view, the use of Nsp5 as the switch to start inflammation, and the consequent overproduction of the ACE2 receptor, is the probable reason of the increased dangerousness of SARS-CoV-2 with respect to SARS-CoV.

The qualitative model presented in this work recovers the onset of the four fields that correspond to those of each floral organ whorl ofArabidopsisflower, suggesting a mechanism for the generation of the positional information required for the differential expression of the A, B and C identity genes according to the ABC model for organ determination during early stages of flower development. Our model integrates a previous model for the emergence of WUS pattern in the apical meristem, and shows that this pre-pattern is a necessary but not sufficient condition for the posterior information of the four fields predicted by the ABC model. Furthermore, our model predicts that LFY diffusion along the L1 layer of cells is not a necessary condition for the patterning of the floral meristem.

Patterning in plant development is the emergent outcome of the feedback-based interplay between tissue-coupled intracellular regulatory networks and physicochemical fields. This interplay gives rise to dynamics that evolve on a wide spectrum of spatiotemporal scales. This imposes important challenges for computational approaches to model the dynamics of plant development. These challenges are being tackled in recent times by computational and mathematical advances that have made progress in the modelling of regulatory networks, as well as in approaches to couple the latter to physicochemical fields. Efforts in this direction are fundamental to identify the dynamical constraints that emerge from non-cellular autonomous activity in cell-fate decisions and patterning, and requires an understanding of how multi-level and multi-scale processes are coupled. Here, we discuss the use of multi-level modeling and simulation tools for the study of multicellular systems, with emphasis on plants. As illustrative examples, we discuss recent works elucidating the mechanisms that underlie patterning in the root meristem of Arabidopsis thaliana, and in plant responses to environmental conditions.

Background The blockage at the early B lymphoid cell development pathway within the bone marrow is tightly associated with hematopoietic and immune diseases, where the disruption of basal regulatory networks prevents the continuous replenishment of functional B cells. Dynamic computational models may be instrumental for the comprehensive understanding of mechanisms underlying complex differentiation processes and provide novel prediction/intervention platforms to reinvigorate the system. Methods By reconstructing a three-module regulatory network including genetic transcription, intracellular transduction, and microenvironment communication, we have investigated the early B lineage cell fate decisions in normal and pathological settings. The early B cell differentiation network was simulated as a Boolean model and then transformed, using fuzzy logic, to a continuous model. We tested null and overexpression mutants to analyze the emergent behavior of the network. Due to its importance in inflammation, we investigated the effect of NFkB induction at different early B cell differentiation stages. Results While the exhaustive synchronous and asynchronous simulation of the early B cell regulatory network (eBCRN) reproduced the configurations of the hematopoietic progenitors and early B lymphoid precursors of the pathway, its simulation as a continuous model with fuzzy logics suggested a transient IL-7R+ ProB-to-Pre-B subset expressing pre-BCR and a series of dominant B-cell transcriptional factors. This conspicuous differentiating cell population up-regulated CXCR7 and reduced CXCR4 and FoxO1 expression levels. Strikingly, constant but intermediate NFkB signaling at specific B cell differentiation stages allowed stabilization of an aberrant CXCR7+ pre-B like phenotype with apparent affinity to proliferative signals, while under constitutive overactivation of NFkB, such cell phenotype was aberrantly exacerbated from the earliest stage of common lymphoid progenitors. Our mutant models revealed an abnormal delay in the BCR assembly upon NFkB activation, concomitant to sustained Flt3 signaling, down-regulation of Ebf1, Irf4 and Pax5 genes transcription, and reduced Ig recombination, pointing to a potential lineage commitment blockage. Discussion For the first time, an inducible CXCR7hi B cell precursor endowed with the potential capability of shifting central lymphoid niches, is inferred by computational modeling. Its phenotype is compatible with that of leukemia-initiating cells and might be the foundation that bridges inflammation with blockage-related malignancies and a wide range of immunological diseases. Besides the predicted differentiation impairment, inflammation-inducible phenotypes open the possibility of newly formed niches colonized by the reported precursor. Thus, emergent bone marrow ecosystems are predicted following a pro-inflammatory induction, that may lead to hematopoietic instability associated to blockage pathologies.

Asymmetric divisions maintain long-term stem cell populations while producing new cells that proliferate and then differentiate. Recent reports in animal systems show that divisions of stem cells can be uncoupled from their progeny differentiation, and the outcome of a division could be influenced by microenvironmental signals. But the underlying system-level mechanisms, and whether this dynamics also occur in plant stem cell niches (SCN), remain elusive. This article presents a cell fate regulatory network model that contributes to understanding such mechanism and identify critical cues for cell fate transitions in the root SCN. Novel computational and experimental results show that the transcriptional regulator SHR is critical for the most frequent asymmetric division previously described for quiescent centre stem cells. A multi-scale model of the root tip that simulated each cell’s intracellular regulatory network, and the dynamics of SHR intercellular transport as a cell-cell coupling mechanism, was developed. It revealed that quiescent centre cell divisions produce two identical cells, that may acquire different fates depending on the feedback between SHR’s availability and the state of the regulatory network. Novel experimental data presented here validates our model, which in turn, constitutes the first proposed systemic mechanism for uncoupled SCN cell division and differentiation.

Understanding the emergence of biological structures and their changes is a complex problem. On a biochemical level, it is based on gene regulatory networks (GRN) consisting on interactions between the genes responsible for cell differentiation and coupled in a greater scale with external factors. In this work we provide a systematic methodological framework to construct Waddington’s epigenetic landscape of the GRN involved in cellular determination during the early stages of development of angiosperms. As a specific example we consider the flower of the plant Arabidopsis thaliana. Our model, which is based on experimental data, recovers accurately the spatial configuration of the flower during cell fate determination, not only for the wild type, but for its homeotic mutants as well. The method developed in this project is general enough to be used in the study of the relationship between genotype-phenotype in other living organisms.

Arabidopsis naturally occurring populations have allowed for the identification of considerable genetic variation remodeled by adaptation to different environments and stress conditions. Water is a key resource that limits plant growth, and its availability is initially sensed by root tissues. The root&rsquo, s ability to adjust its physiology and morphology under water deficit makes this organ a useful model to understand how plants respond to water stress. Here, we used hyperosmotic shock stress treatments in different Arabidopsis accessions to analyze the root cell morphological responses. We found that osmotic stress conditions reduced root growth and root apical meristem (RAM) size, promoting premature cell differentiation without affecting the stem cell niche morphology. This phenotype was accompanied by a cluster of small epidermal and cortex cells with radial expansion and root hairs at the transition to the elongation zone. We also found this radial expansion with root hairs when plants are grown under hypoosmotic conditions. Finally, root growth was less affected by osmotic stress in the Sg-2 accession followed by Ws, Cvi-0, and Col-0, however, after a strong osmotic stress, Sg-2 and Cvi-0 were the most resilience accessions. The sensitivity differences among these accessions were not explained by stress-related gene expression. This work provides new cellular insights on the Arabidopsis root phenotypic variability and plasticity to osmotic stress.

Resumen La biologia evolutiva se enfoca al estudio de los patrones de variacion fenotipica heredables dentro de las poblaciones y su dinamica en tiempos transgeneracionales. Historicamente, los modelos evolutivos a nivel de las poblaciones se han desarrollado bajo supuestos simples. Dos de ellos particularmente importantes son: 1) el cambio genetico es un indicador directo de la variacion fenotipica y 2) existe aditividad de los impactos geneticos sobre el fenotipo. Un modelo mas certero de evolucion biologica deberia de considerar explicitamente el mapeo entre genotipo y fenotipo y viceversa, ya que los mecanismos que median el desarrollo de los organismos y su interaccion con el ambiente son los que generan la variacion fenotipica. Una perspectiva dinamica no lineal es imprescindible para entender como se genera la variacion fenotipica dado un fondo genetico particular. Dicho de otra manera, es necesario entender los mecanismos sistemicos del mapeo entre genotipo y fenotipo en un contexto ecologico y evolutivo. El campo que comprende este enfoque es el de la Ecologia Evolutiva del Desarrollo (Eco-Evo-Devo), el cual tiene ademas un enfoque sistemico. En Mexico este campo ha crecido de manera incipiente a traves del analisis de los mecanismos de desarrollo con enfoques de biologia de sistemas, principalmente. En este articulo resumimos avances de este campo de estudio en Mexico y cuales son los principales grupos de investigacion en el pais, tanto en plantas como en animales. Tambien evaluamos los impactos biomedicos de tomar esta perspectiva.

In Mexico, the Center of origin and diversity of maize, a daily per capita average of 0.5 kg of maize-based foods are consumed. Approximately 10 million tons of maize is produced in small peasant holdings. Nevertheless, a greater proportion of industrially produced maize-derived products have started to appear in recent years. We traced the presence of transgenes and glyphosate in maize-based foods collected in Mexico and elsewhere as a means to describe the landscape of distribution, abundance, and types of transgenes in maize-derived food in Mexico. Transgenic sequences were present in overall 82% of assayed food categories; while the most widely form of maize consumption in Mexico, tortillas, had recombinant sequences in 90.4% of the samples. Furthermore, we found statistically indistinguishable frequency distributions of transgenes in samples from Mexico and other countries. Additionally, glyphosate was detected in approximately 27.7% of the samples rendered positive for transgenic events tole...

Downstream connection effects on transcription are caused by retroactivity. When biomolecular dynamical systems interconnect retroactivity is a property that becomes important. The biological functional meaning of these effects is increasingly becoming an area of interest. Downstream targets, which are operator binding sites in transcriptional networks, may induce behaviors such as ultrasensitive responses or even represent an undesired issue in regulation. To the best of our knowledge, the role of the binding mechanisms of transcription factors in relation to minimizing – or enhancing – retroactivity effects has not been previously addressed. Our aim is to evaluate retroactivity effects considering how the binding mechanism impacts the number of free functional transcription factor (FFTF) molecules using a simple model via deterministic and stochastic simulations. We study four transcription factor binding mechanisms (BM): simple monomer binding (SMB), dimer binding (DB), cooperative sequential binding (CSB) and cooperative sequential binding with dimerization (CSB_D). We consider weak and strong binding regimes for each mechanism, where we contrast the cases when the FFTF is bound or unbound to the downstream loads. Upon interconnection, the number of FFTF molecules changed less for the SMB mechanism while for DB they changed the most. Our results show that for the chosen mechanisms (in terms of the corresponding described dynamics), retroactivity effects depend on transcription binding mechanisms. This contributes to the understanding of how the transcription factor regulatory function—such as decision making—and its dynamic needs for the response, may determine the nature of the selected binding mechanism.

Plant growth is largely post-embryonic and depends on meristems that are active throughout the lifespan of an individual. Developmental patterns rely on the coordinated spatio-temporal expression of different genes, and the activity of transcription factors is particularly important during most morphogenetic processes. MADS-box genes constitute a transcription factor family in eukaryotes. In Arabidopsis, their proteins participate in all major aspects of shoot development, but their role in root development is still not well characterized. In this review we synthetize current knowledge pertaining to the function of MADS-box genes highly expressed in roots: XAL1, XAL2, ANR1 and AGL21, as well as available data for other MADS-box genes expressed in this organ. The role of Trithorax group and Polycomb group complexes on MADS-box genes' epigenetic regulation is also discussed. We argue that understanding the role of MADS-box genes in root development of species with contrasting architectures is still a challenge. Finally, we propose that MADS-box genes are key components of the gene regulatory networks that underlie various gene expression patterns, each one associated with the distinct developmental fates observed in the root. In the case of XAL1 and XAL2, their role within these networks could be mediated by regulatory feedbacks with auxin.

Computational mechanistic models enable a systems-level understanding of plant development by integrating available molecular experimental data and simulating their collective dynamical behavior. Boolean gene regulatory network dynamical models have been extensively used as a qualitative modeling framework for such purpose. More recently, network modeling protocols have been extended to model the epigenetic landscape associated with gene regulatory networks. In addition to understanding the concerted action of interconnected genes, epigenetic landscape models aim to uncover the patterns of cell state transition events that emerge under diverse genetic and environmental background conditions. In this chapter we present simple protocols that naturally extend gene regulatory network modeling and demonstrate their use in modeling plant developmental processes under the epigenetic landscape framework. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature. The protocols presented here can be applied to any well-characterized gene regulatory network in plants, animals, or human disease.

As sessile organisms, plants must adjust their growth to withstand several environmental conditions. The root is a crucial organ for plant survival as it is responsible for water and nutrient acquisition from the soil and has high phenotypic plasticity in response to a lack or excess of them. How plants sense and transduce their external conditions to achieve development, is still a matter of investigation and hormones play fundamental roles. Hormones are small molecules essential for plant growth and their function is modulated in response to stress environmental conditions and internal cues to adjust plant development. This review was motivated by the need to explore how Arabidopsis thaliana primary root differentially sense and transduce external conditions to modify its development and how hormone-mediated pathways contribute to achieve it. To accomplish this, we discuss available data of primary root growth phenotype under several hormone loss or gain of function mutants or exogenous application of compounds that affect hormone concentration in several abiotic stress conditions. This review shows how different hormones could promote or inhibit primary root development in A. thaliana depending on their growth in several environmental conditions. Interestingly, the only hormone that always acts as a promoter of primary root development is gibberellins.

Biological systems are complex, stochastic, and nonlinear; therefore, understanding how genes map to phenotypes remains a challenge. A complex-systems mechanistic approach, emphasizing relations over associations, is required for understanding the emergence of cell differentiation and morphogenesis during development. An increasing number of contemporary studies that integrate biological data into dynamic, nonlinear, and stochastic models are providing novel explanations for development. Unfortunately, the adaptation of the biological research tradition to such quantitative and interdisciplinary approaches is not straightforward. In an attempt to contribute to this necessary transition, drawing mainly on our own studies as examples, we present here a nontechnical overview article of how such models are helping unravel the emergence of cell differentiation, pattern formation, and morphogenesis. The studies reviewed here suggest that we need to reevaluate how biological causal and functional roles are interpreted.

Differentiation and morphogenetic processes during plant development are particularly robust. At the cellular level, however, plants also show great plasticity in response to environmental conditions, and can even reverse apparently terminal differentiated states with remarkable ease. Can we understand and predict both robust and plastic systemic responses as a general consequence of the non-trivial interplay between intracellular regulatory networks, extrinsic environmental signalling, and tissue-level mechanical constraints? Flower development has become an ideal model system to study these general questions of developmental biology, which are especially relevant to understanding stem cell patterning in plants, animals, and human disease. Decades of detailed study of molecular developmental genetics, as well as novel experimental techniques for in vivo assays in both wild-type and mutant plants, enable the postulation and testing of experimentally grounded mathematical and computational network dynamical models. Research in our group aims to explain the emergence of robust transitions that occur at the shoot apical meristem, as well as flower development, as the result of the collective action of key molecular components in regulatory networks subjected to intra-organismal signalling and extracellular constraints. Here we present a brief overview of recent work from our group, and that of others, focusing on the use of simple dynamical models to address cell-fate specification and cell-state stochastic dynamics during flowering transition and cell-state transitions at the shoot apical meristem of Arabidopsis thaliana. We also focus on how our work fits within the general field of plant developmental modelling, which is being developed by many others.

Understanding the effects of climate change on maize yield in Mexico is important from both a national and international perspective. Maize is Mexico's staple food crop, thus, decrements in national production would strongly compromise food security in the country. Internationally, maize is the most important grain crop in terms of human consumption and the conservation in situ of its germplasm should be a global priority. Mexico harbors half of the known genetic diversity for this crop in the American continent, which is instrumental for future genetic improvement efforts that could generate new, environmentally resilient varieties. In this study, we analyze the link between maize yield and several climate variables in rainfed and irrigated crop areas in Mexico to project yield variations under future climate change scenarios. We used municipality-level data for seven states that account for ∼65% of the annual maize production in Mexico and cover an important amount of national climatic variability. We used public data published by the Mexican government on yield and climate from 2003 to 2015 and built linear models to assess the impact of climate on maize yield. We considered the municipality to be a random effect and accounted for potential autocorrelation in the 13-year time series. We also evaluated how many municipalities reached their states' breakeven point in order to project the geographic areas that will earn higher profits due to increased yields. Our results showed that the municipality had a significant effect on yield, and consequently, our results could not be extrapolated to other geographic areas in the country. We found temperature to be the most influential factor on yield under rainfed conditions, while precipitation was the most influential factor for irrigated crops. Like earlier studies at a global scale, we found higher yield stability for irrigated fields than for rainfed fields when considering different climate change scenarios. Our projections indicate that yields from rainfed fields will be reduced significantly under future scenarios. We argue that average yield data in rainfed fields does not include data on the diversity of native maize varieties or their potentially different responses to changes in the environment. Finally, under current conditions, there are by far more municipalities reaching their breakeven point in rainfed fields than in irrigated fields, suggesting that higher yields do not necessarily translate into greater profits for farmers because costs can also increase depending on the type of agriculture practiced.

The current pandemic has rocked the lives of human beings every-where in ways never imagined, forcing us to question where our civilization is headed. In this article, we explore and discuss scien-tifi c evidence that helps explain recent events in the context of the COVID-19 pandemic.COVID-19 is caused by infection with a zoonotic-origin novel virus, SARS-CoV-2, that is genetically close to two coronavirus types iso-lated in bats. The transmission dynamics to humans from the original and intermediary hosts remain poorly understood, but it is highly likely that the SARS-CoV-2 virus infected humans after undergoing an inter-species transfer from bats to an intermediate species, and from there to human beings. Crossing the species barrier is largely fostered by industrial-scale agricultural practices that simplify original ecosystem connections by reducing biodiversity, facilitating the emergence of new infectious diseases. The scientifi c community has played an exemplary role in responding to this global emergency, working to fi nd timely, relevant solutions for governments and society as a whole. We need to take this opportunity to promote a global and open science that delves into the interrelation-ships of the biological, environmental, social and economic dimen-sions of this and other diseases while questioning current modes of production and their impact on the environment, and thus on human health worldwide. Keywords: Coronavirus infections; communicable diseases; zoonoses; ecosystems; technology, industry, and agriculture; pandemics; global health; Mexico.

Computational mechanistic models enable a systems-level understanding of plant development by integrating available molecular experimental data and simulating their collective dynamical behavior. Boolean gene regulatory network dynamical models have been extensively used as a qualitative modeling framework for such purpose. More recently, network modeling protocols have been extended to model the epigenetic landscape associated with gene regulatory networks. In addition to understanding the concerted action of interconnected genes, epigenetic landscape models aim to uncover the patterns of cell state transition events that emerge under diverse genetic and environmental background conditions. In this chapter we present simple protocols that naturally extend gene regulatory network modeling and demonstrate their use in modeling plant developmental processes under the epigenetic landscape framework. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature. The protocols presented here can be applied to any well-characterized gene regulatory network in plants, animals, or human disease.

Diverse cellular polarization states with different phenotypes and functions are derived from the differentiation of activated CD4+ T naïve lymphocytes in the presence of particular cytokines. In addition, conversion of polarized cells to phenotypes different from that originally induced has been documented, highlighting the capacity of the immune response for adaptation to changing circumstances. In a recent study, we proposed a minimal Boolean regulatory network of CD4+ T differentiation that incorporates transcription factors, signaling pathways, and autocrine and exogenous cytokines. The qualitative model effectively reproduced the main polarized phenotypes of CD4+ T cells and several of the plasticity events reported in the literature. Yet, the amount and the expression of cytokines relative to expression of other factors influence CD4+ T cell transitions. In this paper, we have extended the Boolean network to a continuous model that allows us to assess the effect of quantitative differences in the concentrations and combinations of exogenous and endogenous cytokines, as well as diverse levels of transcription factors expression, in order to assess the role of intracellular and extracellular components in CD4+ T differentiation and plasticity. Interestingly, the model predicts either abrupt or gradual differentiation patterns between observed phenotypes depending on critical concentrations of single or multiple environmental cytokines. Plastic changes induced by environmental cytokines were observed in conditions of partial phenotype polarization in the Th1/Th2 transition. On the other hand, the Th17/iTreg transition was highly dependent on cytokine concentrations in the environment. Thus, modeling shows how the concentration of exogenous factors, the degree of initial polarization, and cell heterogeneity, may determine the differentiation and plasticity capacity of CD4+ T cells. The model and results presented here are useful to further understand system-level mechanisms underlying observed patterns of CD4+ T differentiation and plasticity.

The Arabidopsis thaliana (hereafter Arabidopsis) root has become a useful model for studying how organ morphogenesis emerge from the coordination and balance of cell proliferation and differentiation, as both processes may be observed and quantified in the root at different stages of development. Hence, being able to objectively identify and delimit the different stages of root development has been very important. Up to now, three different zones along the longitudinal axis of the primary root of Arabidopsis, have been identified: the root apical meristematic zone (RAM) with two domains [the proliferative (PD) and the transition domain (TD)], the elongation zone (EZ) and the maturation zone (MZ). We previously reported a method to quantify the length of the cells of the meristematic and the elongation zone, as well as the boundaries or transitions between the root domains along the growing part of the Arabidopsis root. In this study, we provide a more accurate criterion to identify the MZ. Traditionally, the transition between the EZ to the MZ has been established by the emergence of the first root-hair bulge in the epidermis, because this emergence coincides with cell maturation in this cell type. But we have found here that after the emergence of the first root-hair bulge some cells continue to elongate and we have confirmed this in three different Arabidopsis ecotypes. We established the limit between the EZ and the MZ by looking for the closest cortical cell with a longer length than the average cell length of 10 cells after the cortical cell closest to the epidermal cell with the first root-hair bulge in these three ecotypes. In Col-0 and Ws this cell is four cells above the one with the root hair bulge and, in the Ler ecotype, this cell is five cells above. To unambiguously identifying the site at which cells stop elongating and attain their final length and fate at the MZ, we propose to calculate the length of completely elongated cortical cells counting 10 cells starting from the sixth cell above the cortical cell closest to the epidermal cell with the first root-hair bulge. We validated this proposal in the three ecotypes analyzed and consider that this proposal may aid at having a more objective way to characterize root phenotypes and compare among them.

Network biology aims to understand cell behavior through the analysis of underlying complex biomolecular networks. Inference of condition-specific interaction networks from epigenomic data enables the characterization of the structural plasticity that regulatory networks can acquire in different tissues of the same organism. From this perspective, uncovering specific patterns of variation by comparing network structure among tissues could provide insights into systems-level mechanisms underlying cell behavior. Following this idea, here we propose an empirical framework to analyze mammalian tissue-specific networks, focusing on characterizing and contrasting their structure and behavior in response to perturbations. We structurally represent the state of the cell/tissue by condition specific transcription factor networks generated using DNase-seq chromatin accessibility data, and we profile their systems behavior in terms of the structural robustness against random and directed perturbations. Using this framework, we unveil the structural heterogeneity existing among tissues at different levels of differentiation. We uncover a novel and conserved systems property of regulatory networks underlying embryonic stem cells (ESCs): in contrast to terminally differentiated tissues, the promiscuous regulatory connectivity of ESCs produces a globally homogeneous network resulting in increased structural robustness. We show that this property is associated with a more permissive, less restrictive chromatin accesibility state in ESCs. Possible biological consequences of this property are discussed.

SUMMARYAnalyses of the geographic patterns of wild species abundance have been carried out in studies ranging from those interested in hot-spots for biodiversity and conservation to basic ecological analyses. Based on the methodological approaches used, the present study searched for areas of higher yield among native races of maize in Mexico, its centre of origin and diversification. Ecological theory suggests that population fitness, and thus abundance, is maximal at the centroid of the multi-dimensional ecological niche of a particular species, and decreases progressively as distance from it increases. In the present study, yield was used instead of abundance, assuming it to be higher under optimal environmental conditions. It was assessed whether nine Mexican maize races exhibited higher yields in areas that are ecologically closer to their niche centroid (NC), or a niche optimum (NO) that did not always coincide with the geometric centroid. Environmental and geographical clusters for each race were also created to identify additional NOs in widely distributed races. All races showed significant correlations between yield and distance, both to the NC or NOs, but in only six of them was the chosen model better than the null model. Three races and two sub-groups were selected for projection under climate change conditions: Celaya (R2= 0·288), Celaya 3 (R2= 0·774), Vandeño (R2= 0·277) and Vandeño 2 (R2= 0·466) and Tepecintle (R2= 0·537). The Celaya race improved with environmental clustering, while Vandeño improved under geographical clustering. Finally, Tepecintle was projected at a race level. Projections under climate change suggested some potential areas for high yields in the future. It was concluded that the approach used in the present paper, considering the distance to NC/NO as a predictor of maize landrace yield, may contribute important information to agro-ecological projects.

Current advances indicate that epigenetic mechanisms play important roles in the regulatory networks involved in plant developmental responses to environmental conditions. Hence, understanding the role of such components becomes crucial to understanding the mechanisms underlying the plasticity and variability of plant traits, and thus the ecology and evolution of plant development. We now know that important components of phenotypic variation may result from heritable and reversible epigenetic mechanisms without genetic alterations. The epigenetic factors Polycomb group (PcG) and Trithorax group (TrxG) are involved in developmental processes that respond to environmental signals, playing important roles in plant plasticity. In this review, we discuss current knowledge of TrxG and PcG functions in different developmental processes in response to internal and environmental cues and we also integrate the emerging evidence concerning their function in plant plasticity. Many such plastic responses rely on meristematic cell behavior, including stem cell niche maintenance, cellular reprogramming, flowering and dormancy as well as stress memory. This information will help to determine how to integrate the role of epigenetic regulation into models of gene regulatory networks, which have mostly included transcriptional interactions underlying various aspects of plant development and its plastic response to environmental conditions.

A growing body of evidence suggests that alterations in transcriptional regulation of genes involved in modulating development are an important part of phenotypic evolution, and this can be documented among species and within populations. While the effects of differential transcriptional regulation in organismal development have been preferentially studied in animal systems, this phenomenon has also been addressed in plants. In this review, we summarize evidence for cis-regulatory mutations, trans-regulatory changes and epigenetic modifications as molecular events underlying important phenotypic alterations, and thus shaping the evolution of plant development. We postulate that a mechanistic understanding of why such molecular alterations have a key role in development, morphology and evolution will have to rely on dynamic models of complex regulatory networks that consider the concerted action of genetic and nongenetic components, and that also incorporate the restrictions underlying the genotype to phenotype mapping process. Developmental Dynamics 244:1074–1095, 2015. © 2015 Wiley Periodicals, Inc.

Molecular regulation was initially assumed to follow both a unidirectional and a hierarchical organization forming pathways. Regulatory processes, however, form highly interlinked networks with non-hierarchical and non-unidirectional structures that contain statistically overrepresented circuits or motifs. Here, we analyze the behavior of pathways containing non-unidirectional (i.e. bidirectional) and non-hierarchical interactions that create motifs. In comparison with unidirectional and hierarchical pathways, our pathways have a high diversity of behaviors, characterized by the size and number of attractors. Motifs have been studied individually showing that feedback circuit motifs regulate the number and size of attractors. It is less clear what happens in molecular networks that usually contain multiple feedbacks. Here, we find that the way feedback circuits couple to each other (i.e., the combination of the functionalities of feedback circuits) regulate both the number and size of the attractors. We show that the different expected results of epistasis analysis (a method to infer regulatory interactions) are produced by many non-hierarchical and non-unidirectional structures. Thus, these structures cannot be correctly inferred by epistasis analysis. Finally, we show that the combinations of functionalities, combined with other network properties, allow for a better characterization of regulatory structures.

The study of the concerted action of hormones and transcription factors is fundamental to understand cell differentiation and pattern formation during organ development. The root apical meristem of Arabidopsis thaliana is a useful model to address this. It has a stem cell niche near its tip conformed of a quiescent organizer and stem or initial cells around it, then a proliferation domain followed by a transition domain, where cells diminish division rate before transiting to the elongation zone; here, cells grow anisotropically prior to their final differentiation towards the plant base. A minimal model of the gene regulatory network that underlies cell-fate specification and patterning at the root stem cell niche was proposed before. In this study, we update and couple such network with both the auxin and cytokinin hormone signaling pathways to address how they collectively give rise to attractors that correspond to the genetic and hormonal activity profiles that are characteristic of different cell types along A. thaliana root apical meristem. We used a Boolean model of the genetic-hormonal regulatory network to integrate known and predicted regulatory interactions into alternative models. Our analyses show that, after adding some putative missing interactions, the model includes the necessary and sufficient components and regulatory interactions to recover attractors characteristic of the root cell types, including the auxin and cytokinin activity profiles that correlate with different cellular behaviors along the root apical meristem. Furthermore, the model predicts the existence of activity configurations that could correspond to the transition domain. The model also provides a possible explanation for apparently paradoxical cellular behaviors in the root meristem. For example, how auxin may induce and at the same time inhibit WOX5 expression. According to the model proposed here the hormonal regulation of WOX5 might depend on the cell type. Our results illustrate how non-linear multi-stable qualitative network models can aid at understanding how transcriptional regulators and hormonal signaling pathways are dynamically coupled and may underlie both the acquisition of cell fate and the emergence of hormonal activity profiles that arise during complex organ development., Author summary In multicellular development, signaling molecules are essential for the organization of cells into complex differentiated tissues. It is widely acknowledged that tissue or cell context is instructive for the specificity of cell behavior responses, but the underlying system-level mechanisms remain unresolved. The dynamic analysis of multi-stable regulatory network models grounded on experimental information allows the characterization of necessary and sufficient restrictions to recover the steady state gene/hormone configurations that correlate with different cell types or behaviors. Therefore, it is possible to formally understand how the cellular context, that mediates or biases particular regulatory interactions, is established during development. To this end, we proposed a minimal network model that integrates the regulatory cross-talk among the auxin and cytokinin signaling pathways with the main studied transcriptional regulators operating during the establishment and organization of the A. thaliana root apical meristem. We uncovered a regulatory network that represents a system-level mechanism that underlies the acquisition of characteristic activity configurations that correlate with different cell types, and at the same time mediates the readout of a hormone. Our model hence suggests that when a cell acquires a particular cell fate it may also acquire a differential capacity to respond to a particular hormone. This coupling mechanism between cell differentiation and the specificity in the responses to a hormone could be a general system-level mechanism operating in all multicellular eukaryote organisms. The systemic mechanism proposed here could hence contribute at understanding how signaling molecules and gene regulatory networks information processing operate during development. To achieve this understanding, the root meristem proved to be a very useful system.

Stem cells are identical in many scales, they share the same molecular composition, DNA, genes, and genetic networks, yet they should acquire different properties to form a functional tissue. Therefore, they must interact and get some external information from their environment, either spatial (dynamical fields) or temporal (lineage). In this paper we test to what extent coupled chemical and physical fields can underlie the cell's positional information during development. We choose the root apical meristem of Arabidopsis thaliana to model the emergence of cellular patterns. We built a model to study the dynamics and interactions between the cell divisions, the local auxin concentration, and physical elastic fields. Our model recovers important aspects of the self-organized and resilient behavior of the observed cellular patterns in the Arabidopsis root, in particular, the reverse fountain pattern observed in the auxin transport, the PIN-FORMED (protein family of auxin transporters) polarization pattern and the accumulation of auxin near the region of maximum curvature in a bent root. Our model may be extended to predict altered cellular patterns that are expected under various applied auxin treatments or modified physical growth conditions.

Molecular regulation was initially assumed to follow both a unidirectional and a hierarchical organization forming pathways. Regulatory processes, however, form highly interlinked networks with non-hierarchical and non-unidirectional structures that contain statistically overrepresented circuits or motifs. Here, we analyze the behavior of pathways containing non-unidirectional (i.e. bidirectional) and non-hierarchical interactions that create motifs. In comparison with unidirectional and hierarchical pathways, our pathways have a high diversity of behaviors, characterized by the size and number of attractors. Motifs have been studied individually showing that feedback circuit motifs regulate the number and size of attractors. It is less clear what happens in molecular networks that usually contain multiple feedbacks. Here, we find that the way feedback circuits couple to each other (i.e., the combination of the functionalities of feedback circuits) regulate both the number and size of the attractors. We show that the different expected results of epistasis analysis (a method to infer regulatory interactions) are produced by many non-hierarchical and non-unidirectional structures. Thus, these structures cannot be correctly inferred by epistasis analysis. Finally, we show that the combinations of functionalities, combined with other network properties, allow for a better characterization of regulatory structures.

Background Obesity is frequently linked to insulin resistance, high insulin levels, chronic inflammation, and alterations in the behaviour of CD4+ T cells. Despite the biomedical importance of this condition, the system-level mechanisms that alter CD4+ T cell differentiation and plasticity are not well understood. Results We model how hyperinsulinemia alters the dynamics of the CD4+ T regulatory network, and this, in turn, modulates cell differentiation and plasticity. Different polarizing microenvironments are simulated under basal and high levels of insulin to assess impacts on cell-fate attainment and robustness in response to transient perturbations. In the presence of high levels of insulin Th1 and Th17 become more stable to transient perturbations, and their basin sizes are augmented, Tr1 cells become less stable or disappear, while TGFβ producing cells remain unaltered. Hence, the model provides a dynamic system-level framework and explanation to further understand the documented and apparently paradoxical role of TGFβ in both inflammation and regulation of immune responses, as well as the emergence of the adipose Treg phenotype. Furthermore, our simulations provide new predictions on the impact of the microenvironment in the coexistence of the different cell types, suggesting that in pro-Th1, pro-Th2 and pro-Th17 environments effector and regulatory cells can coexist, but that high levels of insulin severely diminish regulatory cells, especially in a pro-Th17 environment. Conclusions This work provides a first step towards a system-level formal and dynamic framework to integrate further experimental data in the study of complex inflammatory diseases. Electronic supplementary material The online version of this article (doi:10.1186/s12918-017-0436-y) contains supplementary material, which is available to authorized users.

The gene regulatory network of floral organ cell fate specification of Arabidopsis thaliana is a robust developmental regulatory module. Although such finding was proposed to explain the overall conservation of floral organ types and organization among angiosperms, it has not been confirmed that the network components are conserved at the molecular level among flowering plants. Using the genomic data that have accumulated, we address the conservation of the genes involved in this network and the forces that have shaped its evolution during the divergence of angiosperms. We recovered the network gene homologs for 18 species of flowering plants spanning nine families. We found that all the genes are highly conserved with no evidence of positive selection. We studied the sequence conservation features of the genes in the context of their known biological function and the strength of the purifying selection acting upon them in relation to their placement within the network. Our results suggest an association between protein length and sequence conservation, evolutionary rates, and functional category. On the other hand, we found no significant correlation between the strength of purifying selection and gene placement. Our results confirm that the studied robust developmental regulatory module has been subjected to strong functional constraints. However, unlike previous studies, our results do not support the notion that network topology plays a major role in constraining evolutionary rates. We speculate that the dynamical functional role of genes within the network and not just its connectivity could play an important role in constraining evolution.

Food security is a key topic for human welfare worldwide. In this context, the agrobiodiversity in centers of origin and diversification (COD) for the world's staple crops will be critical for feeding the world under changing environmental and social conditions. Maize is one of the most widely cultivated cereal and is the staple food for African and Latin-American countries, including its COD: Mexico, harboring more than 60% of the world's diversity for this crop. In this study we implemented a data mining approach that allowed us to evaluate spatial relationships of environmental (altitude, climate, slope and soil) and social factors (education and ethnic groups) with the spatial distribution of Mexican races, as well as the areas that can potentially harbor the highest number of races (PRA). In contrast to commonly used species distribution approaches, the data mining method implemented here allowed the integration of contrasting types of variables and their spatial relationships with the focal entity. Our results indicate that altitude, which is related with climate, was the factor with highest predictive power for most races. However, different factors showed different degrees of association with the spatial distribution of particular races. In any case, the performance of the model increased when using all evaluated factors. In our example study case, the highly vulnerable race Palomero Tolqueno was mainly influenced by climate, implying that climate change might threaten its preservation by reducing the areas with favorable conditions for its cultivation. Importantly, however, for this and other eleven races analyzed in detail, is that the ethnic group was the factor with the greatest predictive power. This finding further reinforces the key importance of in situ conservation by supporting local indigenous communities who are in charge of preserving, adapting to changing challenges and cultivating local races.

The diversity of floral forms in the plant order Zingiberales has evolved through alterations in floral organ morphology. One striking alteration is the shift from fertile, filamentous stamens to sterile, laminar (petaloid) organs in the stamen whorls, attributed to specific pollination syndromes. Here, we examine the role of the SEPALLATA (SEP) genes, known to be important in regulatory networks underlying floral development and organ identity, in the evolution of development of the diverse floral organs phenotypes in the Zingiberales. Phylogenetic analyses show that the SEP-like genes have undergone several duplication events giving rise to multiple copies. Selection tests on the SEP-like genes indicate that the two copies of SEP3 have mostly evolved under balancing selection, probably due to strong functional restrictions as a result of their critical role in floral organ specification. In contrast, the two LOFSEP copies have undergone differential positive selection, indicating neofunctionalization. Reverse transcriptase-polymerase chain reaction, gene expression from RNA-seq data, and in situ hybridization analyses show that the recovered genes have differential expression patterns across the various whorls and organ types found in the Zingiberales. Our data also suggest that AGL6, sister to the SEP-like genes, may play an important role in stamen morphology in the Zingiberales. Thus, the SEP-like genes are likely to be involved in some of the unique morphogenetic patterns of floral organ development found among this diverse order of tropical monocots. This work contributes to a growing body of knowledge focused on understanding the role of gene duplications and the evolution of entire gene networks in the evolution of flower development.

Background Morphogenesis depends on the concerted modulation of cell proliferation and differentiation. Such modulation is dynamically adjusted in response to various external and internal signals via complex transcriptional regulatory networks that mediate between such signals and regulation of cell-cycle and cellular responses (proliferation, growth, differentiation). In plants, which are sessile, the proliferation/differentiation balance is plastically adjusted during their life cycle and transcriptional networks are important in this process. MADS-box genes are key developmental regulators in eukaryotes, but their role in cell proliferation and differentiation modulation in plants remains poorly studied. Methods We characterize the XAL1 loss-of-function xal1-2 allele and overexpression lines using quantitative cellular and cytometry analyses to explore its role in cell cycle, proliferation, stem-cell patterning and transition to differentiation. We used quantitative PCR and cellular markers to explore if XAL1 regulates cell-cycle components and PLETHORA1 (PLT1) gene expression, as well as confocal microscopy to analyse stem-cell niche organization. Key Results We previously showed that XAANTAL1 (XAL1/AGL12) is necessary for Arabidopsis root development as a promoter of cell proliferation in the root apical meristem. Here, we demonstrate that XAL1 positively regulates the expression of PLT1 and important components of the cell cycle: CYCD3;1, CYCA2;3, CYCB1;1, CDKB1;1 and CDT1a. In addition, we show that xal1-2 mutant plants have a premature transition to differentiation with root hairs appearing closer to the root tip, while endoreplication in these plants is partially compromised. Coincidently, the final size of cortex cells in the mutant is shorter than wild-type cells. Finally, XAL1 overexpression-lines corroborate that this transcription factor is able to promote cell proliferation at the stem-cell niche. Conclusion XAL1 seems to be an important component of the networks that modulate cell proliferation/differentiation transition and stem-cell proliferation during Arabidopsis root development; it also regulates several cell-cycle components.